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Su Zhang, Hua-Qian Cai, Yun Ma, Tian-Yue Fan, Ying Zhang, Gang Huang. SmartPipe: Towards Interoperability of Industrial Applications via Computational Reflection[J]. Journal of Computer Science and Technology, 2020, 35(1): 161-178. DOI: 10.1007/s11390-020-9694-z
Citation: Su Zhang, Hua-Qian Cai, Yun Ma, Tian-Yue Fan, Ying Zhang, Gang Huang. SmartPipe: Towards Interoperability of Industrial Applications via Computational Reflection[J]. Journal of Computer Science and Technology, 2020, 35(1): 161-178. DOI: 10.1007/s11390-020-9694-z

SmartPipe: Towards Interoperability of Industrial Applications via Computational Reflection

  • With the advancement of new information technologies, a revolution is being taken place to bring the industry into a new era of intelligent manufacturing. One of the key requirements of intelligent manufacturing is the interoperability of industrial applications. However, it is challenging to realize the interoperability for legacy industrial applications due to 1) the deficient semantic information of data transmitted over heterogeneous communication protocols, 2) the difficulty to understand the complex process of business logic with no source code, and 3) the high cost and potential risk of reengineering the applications. To address the issues, in this paper, we propose an approach named SmartPipe to exposing existing functionalities of an industrial application as APIs without source code while simultaneously allowing the application to remain unchanged. We design a behavioral runtime model (BRM) as the self-representation of the industrial applications, based on which a computational reflection framework is designed to flexibly construct the model and generate APIs that encapsulate specific functionalities. We validate SmartPipe on a real industrial application that controls the spin-draw winding machine. Results show that our approach is effective and more suitable for industrial scenes compared with traditional approaches.
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